app.py

## App.py

import os
import io
# from IPython.display import Image, display, HTML
from PIL import Image
import base64 

from dotenv import load_dotenv, find_dotenv
_ = load_dotenv(find_dotenv()) # read local .env file
hf_api_key = os.environ['HF_TOKEN']

#### Helper function
import requests, json

#Here we are going to call multiple endpoints!
def get_completion(inputs, parameters=None, ENDPOINT_URL=""):
    headers = {
      "Authorization": f"Bearer {hf_api_key}",
      "Content-Type": "application/json"
    }   
    data = { "inputs": inputs }
    if parameters is not None:
        data.update({"parameters": parameters})
    response = requests.request("POST",
                                ENDPOINT_URL,
                                headers=headers,
                                data=json.dumps(data))
    return json.loads(response.content.decode("utf-8"))

def get_img_completion(inputs, parameters=None, ENDPOINT_URL=""):
    headers = {
      "Authorization": f"Bearer {hf_api_key}",
      "Content-Type": "application/json"
    }   
    data = { "inputs": inputs }
    if parameters is not None:
        data.update({"parameters": parameters})
    response = requests.request("POST",
                                ENDPOINT_URL,
                                headers=headers,
                                data=json.dumps(data))
    return response.content
    # return json.loads(response.content.decode("utf-8"))
    

#text-to-image
TTI_ENDPOINT = "https://api-inference.huggingface.co/models/ZB-Tech/Text-to-Image"
# "http://jupyter-api-proxy.internal.dlai/rev-proxy/huggingface/itt"
# os.environ['HF_API_TTI_BASE']
#image-to-text
ITT_ENDPOINT = "https://api-inference.huggingface.co/models/Salesforce/blip-image-captioning-base"
# "http://jupyter-api-proxy.internal.dlai/rev-proxy/huggingface/tti"
# os.environ['HF_API_ITT_BASE']

## Building your game with `gr.Blocks()`

#Bringing the functions from lessons 3 and 4!
def image_to_base64_str(pil_image):
    byte_arr = io.BytesIO()
    pil_image.save(byte_arr, format='PNG')
    byte_arr = byte_arr.getvalue()
    return str(base64.b64encode(byte_arr).decode('utf-8'))

def base64_to_pil(img_base64):
    base64_decoded = base64.b64decode(img_base64)
    byte_stream = io.BytesIO(base64_decoded)
    pil_image = Image.open(byte_stream)
    return pil_image

def captioner(image):
    base64_image = image_to_base64_str(image)
    result = get_completion(base64_image, None, ITT_ENDPOINT)
    return result[0]['generated_text']

def generate(prompt):
    output = get_img_completion(prompt, None, TTI_ENDPOINT)
    image = Image.open(io.BytesIO(output))
    return image
    # result_image = base64_to_pil(output.content)
    # return result_image

### First attempt, just captioning

import gradio as gr 
with gr.Blocks() as demo:
    gr.Markdown("# Describe-and-Generate game 🖍️")
    image_upload = gr.Image(label="Your first image",type="pil")
    btn_caption = gr.Button("Generate caption")
    caption = gr.Textbox(label="Generated caption")
    
    btn_caption.click(fn=captioner, inputs=[image_upload], outputs=[caption])

# gr.close_all()
# demo.launch(share=True)

# ### Let's add generation

with gr.Blocks() as demo:
    gr.Markdown("# Describe-and-Generate game 🖍️")
    image_upload = gr.Image(label="Your first image",type="pil")
    btn_caption = gr.Button("Generate caption")
    caption = gr.Textbox(label="Generated caption")
    btn_image = gr.Button("Generate image")
    image_output = gr.Image(label="Generated Image")
    btn_caption.click(fn=captioner, inputs=[image_upload], outputs=[caption])
    btn_image.click(fn=generate, inputs=[caption], outputs=[image_output])

# gr.close_all()
demo.launch(share=True)

### Doing it all at once

# def caption_and_generate(image):
#     caption = captioner(image)
#     image = generate(caption)
#     return [caption, image]

# with gr.Blocks() as demo:
#     gr.Markdown("# Describe-and-Generate game 🖍️")
#     image_upload = gr.Image(label="Your first image",type="pil")
#     btn_all = gr.Button("Caption and generate")
#     caption = gr.Textbox(label="Generated caption")
#     image_output = gr.Image(label="Generated Image")
#     btn_all.click(fn=caption_and_generate, inputs=[image_upload], outputs=[caption, image_output])

# gr.close_all()
# demo.launch(share=True)

# gr.close_all()